• 시스템엔지니어링학술지
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• 제19권2호
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• pp.126-134
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• 2023

Drones are emerging as a new security threat, and the world is working to reduce them. Detection and identification are the most difficult and important parts of the anti-drone systems. Existing detection and identification methods each have their strengths and weaknesses, so complementary operations are required. Detection and identification performance in anti-drone systems can be improved through the use of artificial intelligence. This is because artificial intelligence can quickly analyze differences smaller than humans. There are three ways to utilize artificial intelligence. Through reinforcement learning-based physical control, noise and blur generated when the optical camera tracks the drone may be reduced, and tracking stability may be improved. The latest NeRF algorithm can be used to solve the problem of lack of enemy drone data. It is necessary to build a data network to utilize artificial intelligence. Through this, data can be efficiently collected and managed. In addition, model performance can be improved by regularly generating artificial intelligence learning data.

• 한국항행학회논문지
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• 제27권3호
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• pp.287-292
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• 2023

고정형 CCTV의 경우 팬-틸트(pan-tilt)와 줌(zoom) 기능을 활용하여 가시범위를 최대화하더라도 음영지역이 발생하는 문제가 있다. 이에 대한 대표적인 해결방안으로 다수의 고정형 CCTV를 운영하는 것이다. 이는 CCTV의 개수와 비례한 다량의 부가장비(예: 전선, 설비, 모니터 등)가 필요하다. 다른 해결방안으로 드론을 활용하는 것이다. 문제는 운영시간에 대하여 고정형 CCTV 대비 훨씬 짧다. 운영시간을 연장하기 위해 다수의 드론을 활용하여 한 대씩 임무를 교대하면서 수행하는 방식이 있다. 이 경우 배터리 충전이 필요한 드론은 드론 포트(drone port)에서 준비상태(재충전 완료)로 재진입하여 연속된 임무가 가능하게 하는 것이다. 본 논문은 고정된 전방을 향한 단안 카메라가 탑재된 초소형 드론을 활용하여 방범용 CCTV의 기능으로 활용될 때, 원격지에서 효율적인 운영과 후속 임무의 원활한 연속 수행을 위한 드론포트에 안정적인 착지를 위한 시스템을 제안하고 구현한다. 그리고 이에 대한 운영을 통해 활용 가능성을 입증한다.

• 대한임베디드공학회논문지
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• 제16권4호
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• pp.129-136
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• 2021

River facilities and port structures require a regular inspection and diagnosis due to obsolescence. Currently, most river facilities are undergoing indirect inspection and diagnosis by divers. The underwater inspections are not feasible due to safety issues of divers and restrictions on working hours and environment. To overcome these issues, it is intended to conduct inspections of river facilities using underwater drones. In this research, an underwater ROV (Remote Operated Vehicle) has been developed, which is a kind of drone with propellers. As a key device of this research, an injection device has been attached to the underwater drone to conduct an operation test, a stable operation test of an underwater drone, and a test of attached sensors. The river facility inspection can be carried out optimally using the hovering control of the drone and injection systems. With the developed ROV system, hovering test and injection test have been performed to verify the feasibility of this development.

• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.117-119
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• 2021

With the development of the industry, the use of drones in specific mission flight is being actively studied. These drones fly a specified path and perform repetitive tasks. if the drone system will detect objects in real time, the performance of these mission flight will increase. In this paper, we implement object detection system and mount GPU acceleration to maximize the efficiency of limited device resources with drone video using Tensorflow Lite which enables in-device inference from a mobile device and Mobile SDK of DJI, a drone manufacture. For performance comparison, the average processing time per frame was measured when object detection was performed using only the CPU and when object detection was performed using the CPU and GPU at the same time.

• 한국항행학회논문지
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• 제27권5호
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• pp.685-689
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• 2023

The proposed system in the study aims to detect forest fires in real-time stream data received from the drone-camera. Recently, the number of wildfires has been increasing, and also the large scaled wildfires are frequent more and more. In order to prevent forest fire damage, many experiments using the drone camera and vision analysis are actively conducted, however there were many challenges, such as network speed, pre-processing, and model performance, to detect forest fires from real-time streaming data of the flying drone. Therefore, this study applied image data processing works to capture five good image frames for vision analysis from whole streaming data and then developed the object detection model based on YOLO_v2. As the result, the classification model performance of forest fire images reached upto 93% of accuracy, and the field test for the model verification detected the forest fire with about 70% accuracy.

• 한국컴퓨터정보학회논문지
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• 제25권6호
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• pp.9-15
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• 2020

본 논문에서는 4차 산업혁명의 대표 기술 중 하나인 드론(무인항공)이 공항 안전 및 사생활 침해를 위협하는 사례를 제시 하고 문제를 해결하기 위해 드론 관제 시스템 제안을 기술하였다. 최근 (드론) 무인항공이 심각한 문제를 만들고 있다. 국내의 경우 19년 5월 21일 제주지방항공청에 따르면 같은 달 두 차례에 걸쳐 제주 정석비행장 상공에 드론이 비행하여 항공기 운행에 문제가 발생했고 해외 사례의 경우 영국 개트윅 국제공항 활주로 부근에 출현한 드론 때문에 항공기의 이착륙이 잠시 멈추는 소동이 발생하였으며, 또한 드론을 활용하여 개인의 사생활을 도촬 하는 등 여러 문제가 발생되고 있다. 본 논문은 드론(무인항공)에 Access Point(이하 AP) 트랜스폰더를 장착하여 드론의 비행정보(좌표, 고도, 장애 상태)를 원하는 불특정 다수가 드론 AP에 접근하여 드론의 비행정보를 수신 받고, 수신 받은 불특정 다수의 드론 AP 비행정보를 수집, 취합하여 유저 인터페이스 화면에 현 시점에 운행 중인 드론의 정보를 제공한다. 안전한 드론(무인항공)을 운행하기 위해 AP 트랜스폰더를 제안하고 드론의 비행 정보 송, 수신 및 데이터 수집 및 취합 실험을 수행한다[1-3].

• 디지털산업정보학회논문지
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• 제14권4호
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• pp.1-7
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• 2018

The floating sculptures in the form of ad-ballon commonly used ropes in order to hold on. Relatively air flow is much less indoor than outdoor. Users of buoyancy sculptures hope to be able to maintain their desired posture without being fixed. This study applied drone technology to buoyancy sculptures. The drones can be moved vertically and horizontally, and the posture can be maintained, so buoyancy sculptures are easy to apply. Therefore, we have studied the control system of buoyancy sculpture using drone technology. Also, a control system that can maintain the desired posture at a constant height was studied. The overall shape was a light fiber material and helium gas for zero buoyancy to support the sculpture. The system configuration was STM32F103CB from ARM. In addition, the gyro and acceleration, geomagnetic sensors and motors are composed of small and medium size BLDC motors. The scheduling of the control system in the configuration of the control device was carefully considered. Because the role of the whole component becomes very important. The communication between the components is divided into the sensor fusion and the interface communication with the whole controller. Each communication technology is designed to expand. This study was implemented to actively respond from the viewpoint of posture control using the drone technology.

• 대한임베디드공학회논문지
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• 제18권4호
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• pp.141-150
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• 2023

Currently, various companies are actively participating in research and development of drone delivery services. Existing studies do not comprehensively provide integrated functions for future drone delivery services such as mission automation, customer verification, and overcoming performance limitations, which can lead to high manpower demand, reduced user service trust, and potentially overloading low-end devices. Therefore, this study proposes a drone mission automation system (DMAS) using EdgeCPS technology to provide the three aforementioned functions in an integrated manner. Real-world experiments were conducted to evaluate the proposed system, demonstrating that the DMAS components operate according to the specified roles in the delivery scenario. In addition, the system achieved user verification with a similarity of more than 90% in the process of receiving the product, and verified a faster inference speed and a lower resource share than the existing method.

• 한국항행학회논문지
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• 제27권6호
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• pp.740-745
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• 2023

본 연구는 드론의 통신상태 안정화 및 통신거리 확장을 위하여 위성시스템을 활용한 안테나 트래커 시스템 개발을 제시한다. 지상국과 드론 간의 일반적인 고정형 안테나 방식에서 통신 이득을 최대화 하고자 드론과 지상국의 위치정보를 이용하여 자동으로 지상국의 안테나가 드론을 지속적으로 지향할 수 있는 트래커시스템을 개발하였다. 안테나 트래커를 활용하여 통신 상태 안정화를 개선하고 통신거리를 확장함으로써 드론산업 고도화를 가져올 수 있을 것으로 기대된다.

• 대한임베디드공학회논문지
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• 제18권2호
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• pp.75-80
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• 2023

Unmanned drone stations for automatic charging have been developed in order to overcome the flying time limitation of rotary wing drones. Since the drone stations is an unmanned operating system, each of the drones will be required to have a high degree of landing accuracy. Drone precision landing has been mainly studied depended on image processing technologies, but the image processing systems make several problems, such as the mission weight, the drone cost, and the development complexity increases, and the flight time decrease. Thus, this paper researched accuracy of precision landing based on RTK (real time kinetics) for rotary wing drones. For the experiments of RTK based precision landing, a drone repeatedly performed three missions. The survey accuracies of the RTK about missions respectively were set as 0.3, 0.2, and 0.1 meters. Each mission has one take-off point, two way-points and one landing-point, and was repeated ten times. The experiment results revealed landing error distance means of around 0.258, 0.12 and 0.057 meters on each of RTK setting.